The benefits of peer transparency in safe workplace operation post pandemic lockdown

TL;DR

This study uses mathematical modeling to show that transparency among workers in post-pandemic workplaces enhances productivity and reduces infection rates, suggesting policy measures to promote such behavior.

Contribution

It introduces a playable, adaptable SEIR model to analyze the impact of worker transparency on health and productivity in workplace settings.

Findings

Transparency increases productivity.

Transparency reduces infection rates.

Playable model allows scenario testing.

Abstract

The benefits, both in terms of productivity and public health, are investigated for different levels of engagement with the test, trace and isolate procedures in the context of a pandemic in which there is little or no herd immunity. Simple mathematical modelling is used in the context of a single, relatively closed workplace such as a factory or back-office where, in normal operation, each worker has lengthy interactions with a fixed set of colleagues. A discrete-time SEIR model on a fixed interaction graph is simulated with parameters that are motivated by the recent COVID-19 pandemic in the UK during a post-peak phase, including a small risk of viral infection from outside the working environment. Two kinds of worker are assumed, transparents who regularly test, share their results with colleagues and isolate as soon as a contact tests positive for the disease, and opaques who do none of these. Moreover, the simulations are constructed as a ``playable model" in which the transparency level, disease parameters and mean interaction degree can be varied by the user. The model is analysed in the continuum limit. All simulations point to the double benefit of transparency in maximising productivity and minimising overall infection rates. Based on these findings, public policy implications are discussed on how to incentivise this mutually beneficial behaviour in different kinds of workplace, and simple recommendations are made.